Genome Editing Scientist--Bioinformatics · Bayer Crop Science

Sat, 25 Apr 2026 14:08:21 GMT
Engineering

Bayer Crop Science · Chesterfield · $94,480.00 - $141,720.00 · onsite

At Bayer Crop Science, we're seeking a Genome Editing Scientist--Bioinformatics to join our team. As a key member of our Biotechnology R&D department, you will enable data-driven decisions on target selection, experimental design, and editing outcome interpretation by developing reproducible analyses, predictive models, and clear visualizations. You will partner closely with molecular and structural biology colleagues to translate biological questions into computational strategies and to connect prediction with experimental validation.

Your primary responsibilities will include:

Building and maintaining reproducible pipelines and integrated datasets to evaluate and optimize editing tool performance across germplasm and testing systems;

Developing and applying statistical and machine learning models and metrics to quantify drivers of editing efficiency and precision and to compare tool variants across genomic contexts;

Developing computational approaches to improve the design of precise editing components, including guide and target selection and constraint-aware design;

Analyzing large-scale sequencing datasets to characterize editing outcomes, fidelity, and error modes, and generating clear visualizations and decision-ready summaries;

Partnering with molecular and structural biology teams to design experiments, define analysis plans, and translate multi-modal data into actionable recommendations for tool development;

Collaborating closely with genomics, functional genomics, and digital/data science stakeholders to ensure that tools, pipelines, and analyses are scalable, robust, and aligned with broader platform needs.

To succeed in this role, you will possess a PhD in bioinformatics, computational biology, genomics, or a related field, or a Master's degree with 3+ years of additional relevant experience. You will have strong programming skills in languages relevant to biological data analysis, such as Python and R, and experience analyzing genome editing NGS datasets. You will also have knowledge of statistical methods for analyzing editing precision and efficiency, and the ability to clearly communicate underlying assumptions and limitations.

Preferred qualifications include experience applying GenAI and large language models to scientific workflows, background in protein structure prediction and analysis, and experience with chromatin accessibility and structure analysis.